Knowledge and Reasoning

Base Knowledge

Introduction to AI (agents)

Teaching Methodologies

Powerpoint slides and some demonstration vídeos, complemented with application exercices
Problem resolution
Small project implementation based on development tools

Learning Results

To know and understand the tools for developing expert systems, case based reasoning, uncertainty representation, neural and Bayesian networks. To implement systems based on these models.
Capacity for using the tools above described within a short time period. Capacity for identifying problems that can be solved with these kind of systems in real situations. Knowledge acquisition. Understanding the application of expert systems, case based reasoning, fuzzy systems, probability based systems, neural and Bayesian networks.

Program

Neural Networks
Introduction to ES’s
Case Based Reasoning
Uncertainty / Certainty factors and MYCIN /    Fuzzy sets and Mamdani inference
Development tools
Bayesian Networks

Practical Classes: Problems about all the subjects

Labs: Practical works woth Matlab, Drools and GENIE
Final Practical evaluation work

Curricular Unit Teachers

Internship(s)

NAO